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Pixel-perfect HTML to PDF conversion with automatic RTL and Hebrew language support. \n \n Renders using Chrome headless engine with full CSS3/HTML5 support, including Flexbox, Grid, custom fonts, and JavaScript execution \n Automatic right-to-left direction detection for Hebrew, Arabic, and other RTL languages; includes --rtl flag for forced RTL mode \n Configurable page formats (A4, Letter, Legal, A3, A5), orientation, margins, scale, and optional headers/footers \n Requires one-time npm setup

Dual-engine OCR for extracting text from scanned PDFs and images with local or cloud processing. \n \n Supports RapidOCR (local, free, no API key) and SiliconFlow API (cloud-based, high precision) with automatic fallback when local engine fails \n Handles scanned PDFs and multiple image formats (JPG, PNG, BMP, GIF, TIFF, WEBP) with Chinese and English text recognition \n Preserves text order and structure; automatically converts PDF pages to images for processing \n Batch processing capability f

Convert PDF files to Markdown with automatic detection of native text vs scanned documents. \n \n Supports three conversion modes: auto-detect (default), native text extraction, and OCR for scanned PDFs \n Fast JavaScript-based processing with no system dependencies; returns JSON output with page count and conversion mode \n Handles basic table structure preservation and works cross-platform on Windows, macOS, and Linux \n OCR for scanned documents requires optional tesseract.js setup; complex m

Natural-language PDF editing through command-line instructions on specific pages. \n \n Accepts plain-English edit commands targeting individual PDF pages, such as text changes, corrections, and formatting adjustments \n Requires the nano-pdf CLI tool installed via uv or pip \n Page numbering may vary by version; verify output carefully as results can be off-by-one depending on configuration \n

PDF OCR技能用于从影印版PDF文件和图片文件中提取文字内容。该技能支持两种OCR引擎：

Create professional PDF documents from markdown with Chinese font support and theme system.

Extract text, tables, and metadata from PDF documents with character-level precision. \n \n Supports text extraction with layout preservation, word-level positioning, and character-level access including font and size metadata \n Includes advanced table detection with customizable strategies (lines, text, explicit) and tolerance tuning for complex layouts \n Provides visual debugging via image rendering with overlays for characters, words, lines, and detected table boundaries \n Handles cropping

将 Markdown 文档转换为专业的苹果设计风格 PDF 白皮书。

Three tasks. One skill.

This skill enables conversion from PDF to editable Word documents using pdf2docx - a Python library that preserves layout, tables, images, and text formatting. Unlike OCR-based solutions, pdf2docx extracts native PDF content for accurate conversion.